Mich Talebzadeh

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Mich Talebzadeh Ph.D. is a British Computer Scientist, author and science advocate based in London, United Kingdom. Mich has been active in relational databases especially SAP Adaptive Server Enterprise (SAP ASE), SAP Replication Server SAP IQ , Oracle , Oracle TimesTen IMDB and Oracle GoldenGate among others. He pioneered Global peer-to-peer replication for front office trading systems for Deutsche Bank. Since then, Mich has moved on to big Data on-premise and in the Cloud. He has created real time trading systems using Apache Kafka, Apache Spark, Hbase, Aerospike, Google BigQuery among others. More recently Mich's work has been on using Kubernetes clustering for Spark, Jenkins, Kafka among others . His interest in architecture stems from the time he was involved in creating peer-to-peer architecture for Financial systems.

Education

1. PhD, High Energy Nuclear Physics, Imperial College of Science and Technology, University of London
2. Diploma of Imperial College, High Energy Nuclear Physics, Imperial College of Science and Technology, University of London
3. BSc(ENG.), Upper Second, Nuclear Engineering, Queen Mary College, University of London

Business career

Mich has over 20 years industry experience working with the top tier banks at the Senior consultancy level, often reporting to the Managing Director, Head of Data Delivery and/or Senior Managers. Past clients include: Deutsche Bank, Bank of America, J.P. Morgan, Barclays, Credit Suisse, HSBC, Lloyds Banking Group among others.

Mich founded a software consultancy company Cloud Technology Partners Ltd in November 2015. As CEO and and Fintech & Multi-cloud Architect for Cloud Technology Partners Ltd, Mich has advised a number of clients including Credit Suisse, Barclaycard, Aerospike, Deutsche Bank, HSBC and Lloyds Banking Group among others. More recently Mich is involved with promising start-up company SparkNex Ltd working on improving Spark launch time in kubernetes cluster by focusing o the diver itself.

Other activities

Mich is an avid contributor to the open source community. He is a long standing member and contributor to Apache Spark, Apache Hive , Apache HBase , Apache Kafka , Apache Zeppelin

In January 2021, Mich was elected as Google Cloud Partner Advantage Member

Key Expertise areas

• Core skills – Hands-on technologist and SME with extensive experience in the Big Data Strategy, architecture, project management, design and development of Big Data solutions and Cloud, within mainly investment banking. Expert programming in SQL, Python, Scala and so forth.
• Business leadership expertise – Managed heterogeneous mix of teams in diverse geographical locations. Acted as business mentor to a few start-ups. Advised and worked closely with a non-EU Country on setting up IT infrastructure to combat Money Laundering under Financial Action Task Force (FATF).
• Industry Experience – Fixed Income, Global Equities, Global Markets, FX, Securities,& Bonds, Risk, Credit Card Processing, Financial Fraud, KYC-AML.
• Success measurements - key performance indicators [KPI], return on investment [ROI], metrics.

Articles

Date Published Article

1. May 2021 Processing Change Data Capture with Spark Structured Streaming
2. January 2021 Technical Analysis of the latest UK House Price Index, Deploying Modern tools
3. January 2021 Read and Write to BigQuery with Spark and IDE from On-Premises
4. December 2020 Creating Random Test Data in Spark using PySpark
5. November 2020 Real Time Analytics in Cloud with on-premises Oracle Data, Spark, PySpark and Google BigQuery Machine Learning
6. July 28 2020 Kids, Lockdown due to Covid-19 and Gaming Addiction
7. March 2020 Launching a volunteer initiative to create a World Class Global Digital Response to the COVID-19 Pandemic
8. December 2019 Build Data pipeline with Airflow to load Oracle data to Aerospike on Prem, Aerospike in Cloud Containers and Google BigQuery table
9. November 2019 The likely impact of implementing IR35 in the UK, my perspective
10. September 2019 The role of the Big Data Architect in the Digital Transformation era
11. April 2019 Real Time Processing of Trade Data with Kafka, Flume, Spark, Hbase and MongoDB
12. March 2019 Simple Technical Analysis to identify Suspicious Banking Transactions
13. March 2019 Real Time Data Streaming into Big Data and Typical Use Cases
14. February 2019 End to End Solution, Using Google Dataproc, Spark SQL and Google BigQuery ML offering for Predictive Analytics and Machine Learning
15. January 2019 Big Data Batch Architecture, Hybrid Cloud Model Considerations
16. December 2018 The Operational Advantages of Spark as a Distributed Processing Framework
17. July 2018 Use of microservices in Real time Data Streaming for Spark Streaming or Apache Flink
18. August 2017 Apache HBase for the impatient
19. October 2016 A Prototype of Lambda Architecture Build for Financial Risk
20. September 2016 The Application of Lambda Architecture to the Financial Risk within the Investment Banking
21. August 2016 A Road Map For Careers in Big Data, Presented by Mich Talebzadeh for Hortonworks
22. July 2016 A Guide to Successful Big Data Implementation
23. July 2016 Presentation in London: Query Engines for Hive: MR, Spark, Tez with LLAP – Considerations!
24. June 2016 A Possible Next Career Move for Relational DBAs
25. May 2016 A Winning Strategy - Running Apache Hive on Spark Execution Engine (part 1)
26. May 2016 Apache Hive Data Warehouse and external indexes
27. April 2016 What is Complex Event Processing (CEP)
28. April 2016 Big Data And the Myth of Hadoop Demise
29. February 2016 Apache Hive 2 is now Released
30. February 2016 The old SQL, the Jewel in the Crown of RDBMS and now Big Data
31. February 2016 Hive on Spark Engine Versus Spark Using Hive Metastore
32. February 2016 ORC File and Storage Index in Hive
33. January 2016 ETL or ELT and the Use Case
34. December 2015 DIY in the Festive Season. How to install and configure Big Data Hadoop in an hour or so
35. December 2015 Apache Hive, Engine processing in memory or on disk
36. December 2015 Getting ready for IFRS 9 and the Big Data Role
37. December 2015 Big Data in Action for those familiar with Relational Databases and SQL
38. November 2015 Technical Architect and the challenge of Big Data Architecture
39. November 2015 Data Grid and Big Data Architecture with Hadoop and Hive
40. November 2015 An Architecture for Real Time Analytics of Big Data
41. June 2012 Use Case Comparison of ORACLE 11gR2 and Sybase ASE 15.7 on Solid State Disks

My Presentations

1. Presentation in London, Aerospike meetup: Beating the fraudsters with real-time monitoring
2. Presentation in London: Query Engines for Hive: MR, Spark, Tez with LLAP – Considerations!
3. Presentation in London, Mich Talebzadeh for Hortonworks: A Road Map For Careers in Big Data, Proceedings

Author

Mich has authored a number of books including:

• Sybase Transact SQL Programming Guidelines and Best Practices
• A Practitioner’s Guide to Upgrading to Sybase ASE 15

Awards

SAP/Sybase Gold Medal Award 2008

References

• Global Peer-to-Peer Data Replication Using Sybase Replication Server, ISUG_02_99
• Real Time Processing of Trade Data with Kafka, Spark Streaming and Aerospike on Prem and in Cloud
• Mich Talebzadeh, Ryan T Putnam Aug 2004, ISBN 978-0975969304 Search this book on .
• Mich Talebzadeh Oct 2009, ISBN 978-0956369307 Search this book on .
• A Winning Strategy: Running the most Critical Financial Data on SAP Sybase ASE 15, https://talebzadehmich.wordpress.com/awards/

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